The Identification of Haptic Invariants in Humans and Their Applications to Robotics - Jörntell, Henrik; Devillard, Alexis; Burdet, Etienne (Multisensory Research, 2025)
When searching for an object in my pocket, I can clearly perceive the edges, shape, and hardness of the items I touch — regardless of which part of my fingers makes contact and despite large sensorimotor noise. What accounts for these perceptual invariants? Vincent Hayward introduced key elements to investigate this question, by (i) analyzing mechanical spatiotemporal invariants emerging from the constraints of skin–body–environment interactions, alongside corresponding neural invariants, as well as (ii) introducing the underlying concept of a plenhaptic function encompassing all haptic effects that could arise from interaction with the environment. This article presents this framework and some key insights into the nature of human haptics it has enabled. Specifically, it reviews evidence that haptic neural sensing relies on distributed dynamic effects produced within the skin and musculoskeletal system, describes how these effects may be encoded in the brain, and demonstrates how this approach can inform the design of versatile and effective haptic sensing for robots.
Keywords: dynamics; haptic; neural; robotics; skin; tactile